TANAMI monitoring of Centaurus A: The complex dynamics in the inner parsec of an extragalactic jet

Context. Centaurus A (Cen A) is the closest radio-loud active galactic nucleus. Very Long Baseline Interferometry (VLBI) enables us to study the spectral and kinematic behavior of the radio jet¿counterjet system on milliarcsecond scales, providing essential information for jet emission and propagation models. Aims. In the framework of the TANAMI monitoring, we investigate the kinematics and complex structure of Cen A on subparsec scales. We have been studying the evolution of the central parsec jet structure of Cen A for over 3.5 years. The proper motion analysis of individual jet components allows us to constrain jet formation and propagation and to test the proposed correlation of increased high-energy flux with jet ejection events. Cen A is an exceptional laboratory for such a detailed study because its proximity translates to unrivaled linear resolution, where one milliarcsecond corresponds to 0.018 pc. Methods. As a target of the southern-hemisphere VLBI monitoring program TANAMI, observations of Cen A are done approximately every six months at 8.4 GHz with the Australian Long Baseline Array (LBA) and associated telescopes in Antarctica, Chile, New Zealand, and South Africa, complemented by quasi-simultaneous 22.3 GHz observations. Results. The first seven epochs of high-resolution TANAMI VLBI observations at 8.4 GHz of Cen A are presented, resolving the jet on (sub-)milliarcsecond scales. They show a differential motion of the subparsec scale jet with significantly higher component speeds farther downstream where the jet becomes optically thin. We determined apparent component speeds within a range of 0.1c to 0.3c and identified long-term stable features. In combination with the jet-to-counterjet ratio, we can constrain the angle to the line of sight to theta approx 12deg-45deg. Conclusions. The high-resolution kinematics are best explained by a spine-sheath structure supported by the downstream acceleration occurring where the jet becomes optically thin. On top of the underlying, continuous flow, TANAMI observations clearly resolve individual jet features. The flow appears to be interrupted by an obstacle causing a local decrease in surface brightness and circumfluent jet behavior. We propose a jet-star interaction scenario to explain this appearance. The comparison of jet ejection times to high X-ray flux phases yields a partial overlap of the onset of the X-ray emission and increasing jet activity, but the limited data do not support a robust correlation

Isotopic measurements in water vapor, precipitation, and seawater during EUREC4^4A

n early 2020, an international team set out to investigate trade-wind cumulus clouds and their coupling to the large-scale circulation through the field campaign EUREC$^4$A: ElUcidating the RolE of Clouds-Circulation Coupling in ClimAte. Focused on the western tropical Atlantic near Barbados, EUREC$^4$A deployed a number of innovative observational strategies, including a large network of water isotopic measurements collectively known as EUREC$^4$A-iso, to study the tropical shallow convective environment. The goal of the isotopic measurements was to elucidate processes that regulate the hydroclimate state – for example, by identifying moisture sources, quantifying mixing between atmospheric layers, characterizing the microphysics that influence the formation and persistence of clouds and precipitation, and providing an extra constraint in the evaluation of numerical simulations. During the field experiment, researchers deployed seven water vapor isotopic analyzers on two aircraft, on three ships, and at the Barbados Cloud Observatory (BCO). Precipitation was collected for isotopic analysis at the BCO and from aboard four ships. In addition, three ships collected seawater for isotopic analysis. All told, the in situ data span the period 5 January–22 February 2020 and cover the approximate area 6 to 16° N and 50 to 60° W, with water vapor isotope ratios measured from a few meters above sea level to the mid-free troposphere and seawater samples spanning the ocean surface to several kilometers depth. This paper describes the full EUREC$^4$A isotopic in situ data collection – providing extensive information about sampling strategies and data uncertainties – and also guides readers to complementary remotely sensed water vapor isotope ratios. All field data have been made publicly available even if they are affected by known biases, as is the case for high-altitude aircraft measurements, one of the two BCO ground-based water vapor time series, and select rain and seawater samples from the ships. Publication of these data reflects a desire to promote dialogue around improving water isotope measurement strategies for the future. The remaining, high-quality data create unprecedented opportunities to close water isotopic budgets and evaluate water fluxes and their influence on cloudiness in the trade-wind environment. The full list of dataset DOIs and notes on data quality flags are provided in Table 3 of Sect. 5 (“Data availability”)

Hub-Centered Gene Network Reconstruction Using Automatic Relevance Determination

Network inference deals with the reconstruction of biological networks from experimental data. A variety of different reverse engineering techniques are available; they differ in the underlying assumptions and mathematical models used. One common problem for all approaches stems from the complexity of the task, due to the combinatorial explosion of different network topologies for increasing network size. To handle this problem, constraints are frequently used, for example on the node degree, number of edges, or constraints on regulation functions between network components. We propose to exploit topological considerations in the inference of gene regulatory networks. Such systems are often controlled by a small number of hub genes, while most other genes have only limited influence on the network's dynamic. We model gene regulation using a Bayesian network with discrete, Boolean nodes. A hierarchical prior is employed to identify hub genes. The first layer of the prior is used to regularize weights on edges emanating from one specific node. A second prior on hyperparameters controls the magnitude of the former regularization for different nodes. The net effect is that central nodes tend to form in reconstructed networks. Network reconstruction is then performed by maximization of or sampling from the posterior distribution. We evaluate our approach on simulated and real experimental data, indicating that we can reconstruct main regulatory interactions from the data. We furthermore compare our approach to other state-of-the art methods, showing superior performance in identifying hubs. Using a large publicly available dataset of over 800 cell cycle regulated genes, we are able to identify several main hub genes. Our method may thus provide a valuable tool to identify interesting candidate genes for further study. Furthermore, the approach presented may stimulate further developments in regularization methods for network reconstruction from data

Drum Synthesis and Rhythmic Transformation with Adversarial Autoencoders

Creative rhythmic transformations of musical audio refer to automated methods for manipulation of temporally-relevant sounds in time. This paper presents a method for joint synthesis and rhythm transformation of drum sounds through the use of adversarial autoencoders (AAE). Users may navigate both the timbre and rhythm of drum patterns in audio recordings through expressive control over a low-dimensional latent space. The model is based on an AAE with Gaussian mixture latent distributions that introduce rhythmic pattern conditioning to represent a wide variety of drum performances. The AAE is trained on a dataset of bar-length segments of percussion recordings, along with their clustered rhythmic pattern labels. The decoder is conditioned during adversarial training for mixing of data-driven rhythmic and timbral properties. The system is trained with over 500000 bars from 5418 tracks in popular datasets covering various musical genres. In an evaluation using real percussion recordings, the reconstruction accuracy and latent space interpolation between drum performances are investigated for audio generation conditioned by target rhythmic patterns

Lernen von Probabilistischen Modellen zum Ableiten Genregulatorischer Netzwerke

Among the key objectives of gene regulatory network (GRN) inference are the analysis of time series, development of suitable workflows to find new regulatory relations, and the integration of heterogeneous data sources. This thesis contributes to the analysis of gene expression time series, by both the integration of prior knowledge about network structures, known interactions, as well as suitable data discretization. Additionally, to the development of an easily adaptable analysis workflow to predict new interactions, and the integration, representation and analysis of large-scale, biological data from experiments and predictions.Zu den Kernaufgaben der Inferenz von genregulatorischen Netzwerken (GRN) zählt die Analyse von Zeitreihen, das Entwickeln geeigneter Workflows für das Auffinden neuer regulatorischer Abhängigkeiten sowie die Integration von heterogenen Datenquellen. Diese Arbeit beschäftigt sich mit der Analyse von Genexpressions-Zeitreihen mittels Integration von Vorwissen über die Netzwerkstruktur, bekannten Interaktionen, sowie geeigneter Datendiskretisierung. Darüber hinaus mit einem einfach anzupassenden Workflow für die Vorhersage neuer Interaktionen und der Integration, Darstellung und Analyse von hochskalierenden, biologischen Daten aus Experimenten und Vorhersagen

Zur rekonstruktiven Untersuchung von Schule und Unterricht

Digitalisierung fungiert aktuell als bedeutender Schwerpunkt in der Schul- und Unterrichtsforschung. Entsprechend vielfältig erscheinen auch die methodologischen Ansätze und methodischen Verfahren, mit denen das Geschehen in digitalisierten Bildungskontexten in spezifischer Weise perspektiviert wird. Im vorliegenden Beitrag werden in einem ersten Schritt Charakteristika herausgestellt, die Ansätze rekonstruktiv-sinnverstehender Forschung, wie sie von den Beiträgen in diesem Band vertreten werden, in methodologischer Hinsicht kennzeichnen und von anderen Schwerpunkten digitalisierungsbezogener Forschung zum Schul- und Unterrichtsgeschehen abgrenzen (1). In welcher Weise sich die im Band vertretenen methodologischen Orientierungen und methodischen Ansätze selbst wiederum voneinander unterscheiden, wird in einem zweiten Kapitel skizziert (2). Welche Anschlussoptionen sich davon ausgehend für eine gegenstandsangemessene Weiterentwicklung von rekonstruktiven Forschungsansätzen zu Digitalisierung in Schule und Unterricht ergeben, wird in einem abschließenden Kapitel umrissen (3). (DIPF/Orig.

Perception of riverscapes: sensual experience and knowledge

International audienc

Perception of riverscapes: sensual experience and knowledge

International audienc

Determination of integral fast fission cross sections (n,f) of 238U, 237Np, and 242Pu in a directed fission neutron beam at FRM II, Garching

Small samples of 238U, 237Np, and 242Pu wereirradiated in a focused beam of fission neutrons at theForschungsneutronenquelle Heinz Maier-Leibnitz, FRM IIin Garching, Germany. Decay measurements after irradiationrevealed a number of fission products produced. Usingtabulated cumulative fission yields enabled determinationof integral fission cross sections of the isotopes. Crosssections (n,f) for 238U, 237Np and 242Pu were determined as0.38 ± 0.04, 3.17 ± 0.25, and 2.15 ± 0.30 barnrespectively